Impact of Large Language Models of Code on Fault Localization

Identifying the point of error is imperative in software debugging. Traditional fault localization (FL) techniques rely on executing the program and using the code coverage matrix in tandem with test case results to calculate a suspiciousness score for each method or line. Recently, learning-based F...

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Vydané v:	2025 IEEE Conference on Software Testing, Verification and Validation (ICST) s. 302 - 313
Hlavní autori:	Ji, Suhwan, Lee, Sanghwa, Lee, Changsup, Han, Yo-Sub, Im, Hyeonseung
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 31.03.2025
Predmet:	Benchmark testing Codes Computer architecture Deep Learning Fault Localization Feature extraction Fine-Tuning Large Language Model of Code Large language models Location awareness Software debugging Software engineering Software testing Source coding Vulnerability Detection
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